• Journal of Environmental Health Sciences
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• v.45 no.5
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• pp.457-464
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• 2019

Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using $TOPKAT^{(R)}$, OECD toolbox, and $Derek^{(R)}$, all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.293-297
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• 2013

Background: : Chemotherapy-induced thrombocytopenia (CIT) is an important cause of morbitity in patients with cancer. Aim: To investigate the effect of the baseline plasma D-dimer level, an important marker for thrombotic activity, on chemotherapy-induced thrombocytopenia in patients with stage III colon cancer. Materials and Methods: A total of 43 (28 men) eligible patients were divided into two groups according to whether they exhibited chemotherapy-induced thrombocytopenia: Group 1 (n=21) and Group 2 (n=22). Comparison was made using demographic, histopathologic, and laboratory variables. Additionally, baseline plasma D-dimer levels underwent receiver operation characteristics curve analysis, and areas under the curve were calculated. Sensitivity, specificity, and positive and negative likelihood rates were then determined. Results: The incidence of chemotherapy-induced thrombocytopenia had a significant correlation with baseline platelet count (r=0.568, P=0.031) and baseline plasma D-dimer levels (r=0.617, P=0.036). When the cut-off point for the latter was set as 498 ng/mL, the area under the curve was 0.89 (95%CI: 0.74-0.93), the sensitivity was 91.4%, the specificity was 89.7%, the positive likelihood rate was 3.64 and the negative likelihood rate was 0.24 for chemotherapy-induced thrombocytopenia diagnosis. Conclusions: The baseline level of plasma D-dimer could help to differentiate high-risk patients for chemotherapy-induced thrombocytopenia.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.1
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• pp.53-58
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• 2015

Background: The purpose of this study was to assess the the efficacy of oral glutamine (GLN) in prevention of acute radiation-induced esophagitis in patients with lung cancer and determine the predictive role of clinical and dosimetric parameters. Materials and Methods: Thirty-two patients diagnosed with lung cancer were studied prospectively. Sixteen patients (50%) received prophylactic powdered GLN orally in doses of 10g/8h. Patients were treated 2 Gy per fraction daily, 5 days a week. We evaluated the grading of esophagitis daily at the end of each fraction of each treatment day until a cumulative dose of 50 Gy was reached. The primary end point was radiation-induced esophagitis. Results: All patients tolerated GLN well. Toxicity grade, weight loss, serum cytokine levels and esophageal transit times exhibited statistically significant improvement in the GLN receiving group. GLN suppressed the inflammation related to the disease and treatment and reduced toxicity with statistical significance. Conclusions: This study suggests a benefical role of oral GLN use in prevention and/or delay of radiation-induced esophagitis, in terms of esophageal transit time and serum immunological parameters, as well as weight loss.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.2
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• pp.141-158
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• 2019

Objectives: An adverse outcome pathway is a biological pathway that disturbs homeostasis and causes toxicity. It is a conceptual framework for organizing existing biological knowledge and consists of the molecular initiating event, key event, and adverse output. The AOP concept provides intuitive risk identification that can be helpful in evaluating the carcinogenicity of chemicals and in the prevention of cancer through the assessment of chemical carcinogenicity predictions. Methods: We reviewed various papers and books related to the application of AOPs for the prevention of occupational cancer. We mainly used the internet to search for the necessary research data and information, such as via Google scholar(http://scholar.google.com), ScienceDirect(www.sciencedirect.com), Scopus(www.scopus. com), NDSL(http: //www.ndsl.kr/index.do) and PubMed(http://www.ncbi.nlm.nih.gov/pubmed). The key terms searched were "adverse outcome pathway," "toxicology," "risk assessment," "human exposure," "worker," "nanoparticle," "applications," and "occupational safety and health," among others. Results: Since it focused on the current state of AOP for the prediction of toxicity from chemical exposure at work and prospects for industrial health in the context of the AOP concept, respiratory and nanomaterial hazard assessments. AOP provides an intuitive understanding of the toxicity of chemicals as a conceptual means, and it works toward accurately predicting chemical toxicity. The AOP technique has emerged as a future-oriented alternative to the existing paradigm of chemical hazard and risk assessment. AOP can be applied to the assessment of chemical carcinogenicity along with efforts to understand the effects of chronic toxic chemicals in workplaces. Based on these predictive tools, it could be possible to bring about a breakthrough in the prevention of occupational and environmental cancer. Conclusions: The AOP tool has emerged as a future-oriented alternative to the existing paradigm of chemical hazard and risk assessment and has been widely used in the field of chemical risk assessment and the evaluation of carcinogenicity at work. It will be a useful tool for prediction, and it is possible that it can help bring about a breakthrough in the prevention of occupational and environmental cancer.

• Environmental Mutagens and Carcinogens
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• v.21 no.2
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• pp.118-121
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• 2001

The predictive screening of various molecular descriptors for predicting carcinogenic, mutagenic, teratogenic and alkylation activity of chlorinated disinfection byproducts (DBPs) has been investigated for the application of quantitative structure-activity relationships (QSAR). The toxicity index for 29 compounds were computed by the PASS program and active values were employed in this study. Studies show that different descriptors account for the model equation of each genotoxic endpoint and that thermodynamic descriptors significantly played a major role on prediction of endpoints of chlorinated aliphatic compounds.

• Proceedings of the Korean Society of Food Science and Nutrition Conference
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• 2003.11a
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• pp.74-77
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• 2003

A new health paradigm may be evolving that would place emphasis on the positive aspects of diet, identifying components that are physiologically active and that contribute to the prevention of disease onset. It has been increasingly difficult to evaluate the impact of new bioactive materials and food products on the well being of society. Thus, testing systems for both health function and toxicity have become very elaborate, complex, and interrelated, making their interpretation difficult and open to controversy. To select the proper starting materials, to screen the appropriate health functionality and to determine the efficacy of product, a reliable, reproducible, sensitive and predictive assay is required. Particularly, in uitro assay is the first stage in preclinical test on physiologically active materials and have many advantages in terms of time, cost and convenience. However, several factors as well as some limitations should be considered in this assay system. This presentation, therefore, will address the use of in uitro assays for evaluating physiological functionality of foods coupled with general consideration.

• Molecular & Cellular Toxicology
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• v.2 no.3
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• pp.216-221
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• 2006

The cholinesterase-inhibiting organophosphorous (OP) compounds known as nerve agents are highly toxic. The principal toxic mechanism of OP compounds is the inhibition of acethylcholine esterase (AChE) by phosphorylation of its catalytic site. The reversible competitive inhibition of AChE may prevent the subsequent OP intoxication. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) was performed to investigate the relationship between the 29 compounds with structural diversity and their bioactivities against AChE. In particular, predictive models were constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The results indicate reasonable model for CoMFA ($q^{2}=0.453,\;r^{2}=0.697$) and CoMSIA ($q^{2}=0.518,\;r^{2}=0.696$). The presence of steric and hydophobic group at naphtyl moiety of the model may lead to the design of improved competitive inhibitors for organophosphorous intoxication.

• Biomolecules & Therapeutics
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• v.14 no.4
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• pp.183-188
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• 2006

The field of cytochrome P450 pharmacogenomics has progressed rapidly during the past 25 years. Recently, conjugating enzymes including sulfotransferase, acetyltransferase, glucuronosyltransferase and glutathione transferase have been also extensively studied. All the major human drug-metabolizing P450 enzymes and some conjugating enzymes have been identified and cloned, and the major gene variants that cause inter-individual variability in drug response and are related to adverse drug reactions have been identified. This information now provides the basis for the use of predictive pharmacogenomics to yield drug therapies that are more efficient and safer. Today, we understand which drugs warrant dosing based on pharmacogenomics to improve drug treatment. It is anticipated that genotyping could be used to personalize drug treatment for vast numbers of subjects, decreasing the cost of drug treatment and increasing the efficacy of drugs and health in general. It is assumed that such personalized P450 gene-based treatment which is so-called tailor(order)-made drug therapy would be relevant for 10-20% of all drug therapy in the future.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.4
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• pp.281-291
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• 2012

In this study, WET (whole effluent toxicity) test with Skeletonema costatum, Tigriopus japonicus and Paralichthys olivaceus and ERA (environmental risk assessment) were conducted to assess the unacceptable effect on marine ecosystem by emitting the treated discharge water from 'ARA Plasma BWTS' BWMS (ballast water management system) using filtration, Plasma and MPUV module. 34 psu treated discharge water from ARA Plasma BWTS shown slight chronic toxicity effect on the P. olivaceus ($7d-LC_{50}{\Rightarrow}100.00%$ treated discharge water, $7d-LC_{25}{\Rightarrow}85.15%$ treated discharge water). Bromobenzene, chlorobenzene and 4-chlorotoluene in 34 psu treated discharge water from ARA Plasma BWTS were higher than in the background original content of seawater. The PECs (predictive environmental concentrations) of bromobenzene, chlorobenzene and 4-chlorotoluene calculated by MAMPEC (marine antifoulant model to predict environmental concentrations) program (ver. 3.0) were 3.34E-03, 2.10E-03 and 1.73E-03 ${\mu}g\;L^{-1}$, respectively and PNECs (predicted no effect concentrations) of them were 1.6, 0.5 and 1.9 ${\mu}g\;L^{-1}$. The PEC/PNEC ratio of bromobenzene, chlorobenzene and 4-chlorotoluene did not exceed one and 3 substances did not consider as persistence, bioaccumulative and toxic. Therefore, it was suggested that treated discharge water from ARA Plasma BWTS did not pose unacceptable effect on marine ecosystem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.276-278
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• 2022

All drugs have a specific action in the body, and in many cases, drugs are combinated due to complications or new symptoms during existing drug treatment. In this case, unexpected interactions may occur within the body. Therefore, predicting drug-drug interactions is a very important task for safe drug use. In this study, we propose a deep learning-based predictive model that learns using drug information documents to predict drug interactions that may occur when using multiple drugs. The drug information document was created by combining several properties such as the drug's mechanism of action, toxicity, and target using DrugBank data. And drug information document is pair with another drug documents and used as an input to a deep learning-based predictive model, and the model outputs the interaction between the two drugs. This study can be used to predict future interactions between new drug pairs by analyzing the differences in experimental results according to changes in various conditions.